This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Mechanistically diverse enzyme superfamilies represent sets of divergent proteins whose substrates, products and even overall functions can be substantially different. Divergent evolution of such broadly varied chemical reactions can be described by the chemistry-constrained model of enzyme evolution, in which nature re-engineers the ancestral scaffold for a variety of functions by conserving a fundamental chemical capability such as a partial reaction, while evolving variations in substrate binding, and therefore overall chemistry. This renewal proposal has four aims, which extend the progress achieved in the previous grant: 1) Investigate additional mechanistically diverse enzyme superfamilies to determine how the delivery of catalysis is constrained by the common catalytic module in each. We will also detail for each how new catalysts have arisen to perform a variety of functions. We expect the results to reveal general principles of enzyme design utilized in nature and identify specific rules applicable for functional inference and mechanistic understanding for each of the superfamilies investigated. This information will be made available to the scientific community via our ?Structure-Function Linkage Database (SFLD)?. 2) Identify sequence/structural differences that discriminate subgroups/families in characterized superfamilies to achieve more precision in functional inference than can be obtained by prediction of the superfamily-common functions alone. 3) Investigate superfamilies that utilize complex co-factors to learn how such superfamilies differ from the relatively more ?simple? types of superfamilies we have previously studied. These studies will focus first on superfamilies that use FAD cofactors. 4) Lay the groundwork for predicting promiscuity and new chemical reactions that could be supported by the catalytic modules studied in this proposal. Docking methodologies will be used to identify small molecules likely to bind or that could be turned over by superfamily members. The results will be added to the SFLD to aid others in inference of function, identification of inhibitors useful in structural characterization or drug design, and to guide protein engineering/design for applications to human health.